In general, a database management system (DBMS) provides the ability to store, modify and extract information from a database. The database is generally maintained in a mass storage (e.g., hard disk, tape drive, optical disk, and the like). The DBMS may receive one or more queries (e.g., structure query language (SQL) queries) to provide access (e.g., store, modify, extract) to the database. DBMS performance is constrained, among other things, by the architecture on which the DBMS operates, including processor speed and input/output (I/O) speed of mass storage. To meet increasing demand for DBMS performance, vendors have employed improved system architectures and processors, parallel processing (via single or multiple processors), a variety of mass storage techniques, as well as myriad other software and hardware techniques.
While improvements in the foregoing areas have improved DBMS performance considerably, mass storage I/O remains one of the greatest bottlenecks to DBMS performance. More specifically, I/O execution time to access mass storage plays a major role in determining the speed by which queries of the database may be resolved. For example, the resolution of a query may require the creation and manipulation of an associated one or more intermediate files. If an intermediate file is small enough, it is typically cached in file system cache memory. However, if the intermediate file exceeds a size threshold, typically a percentage of file system cache size, then the file is generally stored in slower mass storage device. Therefore, the resolution of the query having intermediate files stored in mass storage, requires the processor to first write the intermediate files to mass storage and later read the intermediate files from mass storage.
In view of the foregoing, the speed with which the intermediate files can be accessed (e.g., written to and read from mass storage) plays an important yet detrimental role in the overall DBMS performance. Consequently, improving the I/O execution time necessary to access the intermediate files ultimately improves DBMS performance in the execution of the query associated with the intermediate files.